Objective To observe CT and MRI manifestations of gastritis cystica profunda(GCP).Methods Seventeen patients with GCP confirmed by operation or biopsy pathology were enrolled,and lesions'CT and MRI manifestations were observed.Results Among 17 cases,16 cases(16/17,94.12％)were found with single lesion and 1(1/17,5.88％)with diffuse multiple lesions.The lesion located in the fundus of stomach in 5 cases(5/17,29.41％),in the body of stomach in 4 cases(4/17,23.53％),in the cardia and antrum of stomach each in 3 cases(3/17,17.65％)and in the pylorus in 1 case(1/17,5.88％),while 1 case(1/17,5.88％)was found with diffused multiple lesions within stomach.Non-enhance CT showed local thickening of gastric wall in 10 cases(10/17,58.82％),all were isodensities,and the mucosa uniformly enhanced in contrast enhance CT(CECT).Predominately cystic lesion in 5 cases(5/17,29.41％)presented as submucosal cystic protrusions,and grew into the stomach cavity with circular or oblong low density in non-enhanced CT,while sandwich enhancement of mucosa was observed in CECT.Among these 5 cases(5/17,29.41％),MRI showed lesion confined to the submucosa with low signal on T1WI and high signal on T2WI,while diffusion weighted imaging showed unrestricted diffusion,and the enhancement pattern was consistent with that of CT in 2 cases.In other 2 cases(2/17,11.77％)with cystic-solid lesion,non-enhanced CT showed soft tissue density,while CECT showed lump-like stratified enhancement.Conclusion CT and MRI manifestations of GCP had certain characteristics.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Experimental teaching is an important component of the course Medical Immunology,which requires the use of experimental animals and the execution of experimental animals by medical students.By applying the carbon dioxide euthanasia system,it can effectively reduce the pain of experimental animals,ensure their welfare,and meet ethical requirements.It can also improve the efficiency of experimental teaching in Medical Immunology,reduce environmental pollution,and promote medical students to estab-lish scientific values and worldviews that pay attention to experimental animals and respect life,which is conducive to becoming future medical service talents.In the experimental teaching of Medical Immunology,the appropriate application of carbon dioxide euthanasia system combined with effective ideological and political construction of the curriculum can further implement the Party's educational policy of cultivating morality and talents,and lay a good foundation for cultivating medical talents with comprehensive knowledge,high skills and excellent quality.

This case report describes the diagnostic and therapeutic management of a 67-year-old fe-male with a 40-year history of Sj?gren disease(SjD)who was hospitalized for evaluation of recurrent fever lasting over one month.The patient's initial diagnosis of SjD was established four decades earlier based on clinical manifestations,serological findings,and evidence of glandular damage.Her clinical presenta-tion included recurrent parotid gland enlargement accompanied by sicca symptoms,notably persistent xerostomia and xerophthalmia,followed by progressive dental caries.Serological studies demonstrated positivity for antinuclear antibodies,anti-SSA/Ro,and anti-α-fodrin antibodies.Objective assessments confirmed significant ocular involvement(Schirmer's test≤5 mm/5 min)and pulmonary interstitial changes on chest CT,consistent with the 2016 American College of Rheumatology and European League Against Rheumatism(ACR/EULAR)classification criteria for SjD.The patient's condition remained sta-ble under low-dose corticosteroids and disease-modifying anti-rheumatic drugs(DMARDs)until the re-cent onset of prolonged fever,necessitating evaluation for fever of unknown origin.Differential diagnoses considered disease flare,infection,and malignancy.The European Sj?gren's Syndrome Disease Activity Index(ESSDAI)score was 5 points,indicating moderate systemic disease activity.Initial laboratory in-vestigations revealed no evidence of infection,and empirical anti-infective therapy proved ineffective.No-tably,despite the absence of lymphadenopathy,laboratory findings including borderline positive IgM λ M-protein,elevated lactate dehydrogenase,hyperferritinemia,and increased β2-microglobulin levels raised suspicion for lymphoproliferative disorders,given the established association between SjD and lymphoma.Bone marrow aspiration showed no significant abnormalities,but PET/CT imaging detected hypermetabolic lesions in the left breast and right distal femur,suggesting potential malignancy.Subse-quent histopathological examination of the breast lesion confirmed non-Hodgkin's lymphoma(NHL),specifically diffuse large B-cell lymphoma(DLBCL)of the germinal center B-cell(GCB)subtype.Treatment with R-CHOP chemotherapy(rituximab,cyclophosphamide,doxorubicin,vincristine,and prednisone)induced complete metabolic remission after three cycles.However,she subsequently developed treatment-related complications,including myelosuppression and pulmonary infection.This case underscores the importance of maintaining a high index of suspicion for atypical site involvement in SjD patients,particularly when lymphoma risk factors are present.Comprehensive differential diagnosis should include lymphoma and other malignancies,and the diagnostic value of PET/CT and histopatholog-ical examination in disease evaluation is emphasized.SjD complicated by breast lymphoma is exceptional-ly rare,and its pathogenesis may involve lymphocytic infiltration,abnormal activation of lymphocytes,formation of ectopic germinal centers in the breast,and eventual malignant transformation.These mecha-nisms require further investigation through clinical and basic research studies.

ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

Objective To observe CT and MRI manifestations of gastritis cystica profunda(GCP).Methods Seventeen patients with GCP confirmed by operation or biopsy pathology were enrolled,and lesions'CT and MRI manifestations were observed.Results Among 17 cases,16 cases(16/17,94.12％)were found with single lesion and 1(1/17,5.88％)with diffuse multiple lesions.The lesion located in the fundus of stomach in 5 cases(5/17,29.41％),in the body of stomach in 4 cases(4/17,23.53％),in the cardia and antrum of stomach each in 3 cases(3/17,17.65％)and in the pylorus in 1 case(1/17,5.88％),while 1 case(1/17,5.88％)was found with diffused multiple lesions within stomach.Non-enhance CT showed local thickening of gastric wall in 10 cases(10/17,58.82％),all were isodensities,and the mucosa uniformly enhanced in contrast enhance CT(CECT).Predominately cystic lesion in 5 cases(5/17,29.41％)presented as submucosal cystic protrusions,and grew into the stomach cavity with circular or oblong low density in non-enhanced CT,while sandwich enhancement of mucosa was observed in CECT.Among these 5 cases(5/17,29.41％),MRI showed lesion confined to the submucosa with low signal on T1WI and high signal on T2WI,while diffusion weighted imaging showed unrestricted diffusion,and the enhancement pattern was consistent with that of CT in 2 cases.In other 2 cases(2/17,11.77％)with cystic-solid lesion,non-enhanced CT showed soft tissue density,while CECT showed lump-like stratified enhancement.Conclusion CT and MRI manifestations of GCP had certain characteristics.

Objective:To analyze the influencing factors of China′s DRG payment system reform(DRG reform) and its hierarchical relationship, for references for the in-depth promotion of China′s medical insurance payment reform.Methods:Relevant literature on DRG reform in China from databases such as CNKI, Wanfang Database, Pubmed, etc, were obtained. Content analysis method was used to extract the influencing factors of DRG reform. The correlation between each influencing factor was determined through expert discussion. An interpretive structural model(ISM) was constructed to analyze the hierarchical relationship of factors influencing DRG reform.Results:After analysis, the influencing factors(12) of DRG reform in China were included such as medical level, hospital management, and medical staff′s cognition and behavior. Among them, the local situation was the deep-level factor affecting DRG reform, 9 factors such as data quality assurance and policy design/implementation were the middle-level factors, and patients′ interests/needs and disease grouping were the surface-level factors.Conclusions:There were many influencing factors on the reform of China′s DRG payment system. It was suggested that relevant management departments in various regions should focus on the actual situation of the locality, take data quality and policy design and implementation as the key points of reform, formulate a scientific and reasonable DRG grouping scheme, safeguard the interests of patients, so as to promote the deepening of DRG reform.

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

Fibrosis, the pathological scarring of vital organs, is a severe and often irreversible condition that leads to progressive organ dysfunction. It is particularly pronounced in organs like the liver, kidneys, lungs, and heart. Despite its clinical significance, the full understanding of its etiology and complex pathogenesis remains incomplete, posing substantial challenges to diagnosing, treating, and preventing the progression of fibrosis. Among the various molecular players involved, platelet-derived growth factor-C (PDGF-C) has emerged as a crucial factor in fibrotic diseases, contributing to the pathological transformation of tissues in several key organs. PDGF-C is a member of the PDGFs family of growth factors and is synthesized and secreted by various cell types, including fibroblasts, smooth muscle cells, and endothelial cells. It acts through both autocrine and paracrine mechanisms, exerting its biological effects by binding to and activating the PDGF receptors (PDGFRs), specifically PDGFRα and PDGFRβ. This binding triggers multiple intracellular signaling pathways, such as JAK/STAT, PI3K/AKT and Ras-MAPK pathways. which are integral to the regulation of cell proliferation, survival, migration, and fibrosis. Notably, PDGF-C has been shown to promote the proliferation and migration of fibroblasts, key effector cells in the fibrotic process, thus accelerating the accumulation of extracellular matrix components and the formation of fibrotic tissue. Numerous studies have documented an upregulation of PDGF-C expression in various fibrotic diseases, suggesting its significant role in the initiation and progression of fibrosis. For instance, in liver fibrosis, PDGF-C stimulates hepatic stellate cell activation, contributing to the excessive deposition of collagen and other extracellular matrix proteins. Similarly, in pulmonary fibrosis, PDGF-C enhances the migration of fibroblasts into the damaged areas of lungs, thereby worsening the pathological process. Such findings highlight the pivotal role of PDGF-C in fibrotic diseases and underscore its potential as a therapeutic target for these conditions. Given its central role in the pathogenesis of fibrosis, PDGF-C has become an attractive target for therapeutic intervention. Several studies have focused on developing inhibitors that block the PDGF-C/PDGFR signaling pathway. These inhibitors aim to reduce fibroblast activation, prevent the excessive accumulation of extracellular matrix components, and halt the progression of fibrosis. Preclinical studies have demonstrated the efficacy of such inhibitors in animal models of liver, kidney, and lung fibrosis, with promising results in reducing fibrotic lesions and improving organ function. Furthermore, several clinical inhibitors, such as Olaratumab and Seralutinib, are ongoing to assess the safety and efficacy of these inhibitors in human patients, offering hope for novel therapeutic options in the treatment of fibrotic diseases. In conclusion, PDGF-C plays a critical role in the development and progression of fibrosis in vital organs. Its ability to regulate fibroblast activity and influence key signaling pathways makes it a promising target for therapeutic strategies aiming at combating fibrosis. Ongoing research into the regulation of PDGF-C expression and the development of PDGF-C/PDGFR inhibitors holds the potential to offer new insights and approaches for the diagnosis, treatment, and prevention of fibrotic diseases. Ultimately, these efforts may lead to the development of more effective and targeted therapies that can mitigate the impact of fibrosis and improve patient outcomes.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.